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Topic: causal-inference-basics
Causal Inference Basics — Advanced
Data Science›Experimentation
Causal Inference Basics

Identification vs estimation, SUTVA, heterogeneous effects, mediation, double robustness, staggered DiD cautions, and design-first causal reasoning for complex product and policy settings. Mix of single-answer and multiple-answer items.

18
36
70%
Advanced
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Causal Inference Basics — Intermediate
Data Science›Experimentation
Causal Inference Basics

DAGs and backdoor adjustment, regression pitfalls, diff-in-diff intuition, instrumental variables, matching, and threats to validity in quasi-experiments. Mix of single-answer and multiple-answer items.

16
32
70%
Intermediate
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Causal Inference Basics — Beginner
Data Science›Experimentation
Causal Inference Basics

Foundations of cause and effect: correlation vs causation, confounding, randomization, counterfactuals, and common observational pitfalls. Mix of single-answer and multiple-answer items.

12
24
70%
Beginner
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